Title :
Depth and normal vector identification of an unknown slope from a UAV using a single camera
Author :
Zhichao Liu ; Jianliang Wang ; Poh Eng Kee ; Sundaram, Suresh
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
Abstract :
This paper presents a novel vision-based system to estimate the normal vector of an unknown slope and the range from a camera fixed on a UAV to the slope using a single camera. An exact point-based image moments model considering the camera´s focal length is presented. Using the model, a fast estimator is designed to estimate the image flow with high precision. The continuous model is then discretized using Taylor series method. Finally, a particle filter is used to obtain a solution to the estimation problem. The whole system estimates simultaneously the normal vector of the unknown slope and the depth from the camera on the UAV to the slope.
Keywords :
autonomous aerial vehicles; image sensors; object detection; robot vision; Taylor series method; UAV; camera focal length; depth vector identification; image flow; normal vector identification; point-based image moments model; unknown slope; vision-based system; Adaptation models; Cameras; Equations; Mathematical model; Observers; Vectors;
Conference_Titel :
Control Conference (ASCC), 2013 9th Asian
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-5767-8
DOI :
10.1109/ASCC.2013.6606215